{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 《python数据可视化之matplotlib实践》\n",
    "## matplotlib可视化学习-chapter-8\n",
    "## 坐标轴高阶应用\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "mpl.rcParams['font.sans-serif'] = ['FangSong']  # 显示中文\n",
    "mpl.rcParams['axes.unicode_minus'] = False # 不使用unicode_minus模式处理坐标轴轴线为负数的情况，\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 两种方法控制坐标轴刻度的显示\n",
    "\n",
    "- ax.set_xticks() or ax.set_yticks()\n",
    "- plt.setp()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "ax1 = plt.subplot(121)\n",
    "ax1.set_xticks(range(0, 251, 50)) # 设置x轴坐标从0到250， 每隔50刻度一次\n",
    "plt.grid(axis='x')  # 注意，网格线是根据tick刻度来画的，有几个刻度画几条线\n",
    "\n",
    "ax2 = plt.subplot(122)\n",
    "ax2.set_xticks([]) # 设置x轴坐标为空\n",
    "ax2.set_yticks(range(-10,10, 5)) # 设置y轴坐标，从-10到10， 每隔5刻度一次\n",
    "plt.grid(axis='x')# 注意，网格线是根据tick刻度来画的，有几个刻度画几条线，该子图没有x刻度，则不会划线\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "t = np.arange(0.05, 10.0, 0.01)\n",
    "s1 = np.exp(t)\n",
    "s2 = np.cos(t)\n",
    "\n",
    "ax1 = plt.subplot(121)\n",
    "ax1.set_xticks(range(0, 251, 50)) # 设置x轴坐标从0到250， 每隔50刻度一次\n",
    "plt.grid(axis='x')  # 注意，网格线是根据tick刻度来画的，有几个刻度画几条线\n",
    "\n",
    "ax2 = plt.subplot(122)\n",
    "ax2.set_xticks([]) # 设置x轴坐标为空\n",
    "ax2.set_yticks(range(-10,10, 5)) # 设置y轴坐标，从-10到10， 每隔5刻度一次\n",
    "plt.grid(axis='x')# 注意，网格线是根据tick刻度来画的，有几个刻度画几条线，该子图没有x刻度，则不会划线\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 方法二 setp\n",
    "\n",
    "ax1 = plt.subplot(221)\n",
    "plt.setp(ax1.get_xticklabels(), visible=True)\n",
    "plt.setp(ax1.get_xticklines(), visible=True)\n",
    "plt.grid(axis='x')\n",
    "\n",
    "ax2 = plt.subplot(222)\n",
    "plt.setp(ax2.get_yticklabels(), visible=False)\n",
    "plt.setp(ax2.get_yticklines(), visible=False)\n",
    "plt.grid(axis='x')\n",
    "\n",
    "ax3 = plt.subplot(223)\n",
    "plt.setp(ax3.get_xticklabels(), visible=False)\n",
    "plt.setp(ax3.get_xticklines(), visible=True)  # 与下面那个子图相比，少了x轴的刻度线\n",
    "plt.grid(axis='x')\n",
    "\n",
    "ax4 = plt.subplot(224)\n",
    "plt.setp(ax4.get_xticklabels(), visible=False)\n",
    "plt.setp(ax4.get_xticklines(), visible=False) # \n",
    "plt.grid(axis='x')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 控制坐标轴的显示\n",
    "通过坐标轴的载体（spines， 轴脊）控制， 轴脊上有刻度线和刻度标签\n",
    "\n",
    "一个图有4个轴脊，上下左右边框"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## 控制坐标轴的显示\n",
    "\n",
    "t = np.arange(0.05, 10.0, 0.01)\n",
    "s1 = np.exp(t)\n",
    "s2 = np.cos(t)\n",
    "\n",
    "ax1 = plt.subplot(121)\n",
    "ax1.spines['right'].set_color('none')  # 不显示上面、右边的刻度线\n",
    "ax1.spines['top'].set_color('none')\n",
    "ax1.set_xlim(-1, 2)\n",
    "ax1.set_ylim(0,3)\n",
    "plt.title(\"$\\exp(x)$\")\n",
    "plt.plot(t, s1)\n",
    "\n",
    "\n",
    "ax2 = plt.subplot(122)\n",
    "ax2.spines['right'].set_color('none')  # 不显示上面、右边的刻度线\n",
    "ax2.spines['top'].set_color('none') \n",
    "\n",
    "ax2.xaxis.set_ticks_position('bottom') # 把刻度线移动到下面，也可以不写（默认）\n",
    "\n",
    "\n",
    "ax2.set_xlim(-1, 2)\n",
    "ax2.set_ylim(0,3)\n",
    "plt.title(\"$\\cos(x)$\")\n",
    "plt.plot(t, s2)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 移动坐标轴位置\n",
    "\n",
    "示例：画一个坐标系，（0,0）为坐标原点\n",
    "\n",
    "方法： \n",
    "- 把右边刻度线、上面刻度线取消（颜色为none）\n",
    "\n",
    "- 再移动左轴和下轴的位置\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OgvIi6ZmrX83IDLWGDh06lB8+fPhEeHh46cyZM4NffPHFKn+0m5vb1eEAZ2dnUaPRCADe3t66ioqKKjHn4MGDnllZWa5ubm7i9QGssrJS8PLysmhoQfHAJssdG1KZrFlbLnFPyYt4uzvTctvDsrZ2iIqKku2zQuv68N2ULpzPKWH6rzFoZZwkK6enksjmmZ0kZUAGtpLS7J3kLfQrl+fBczlMSOjHAe8B9Ev9BpK2y/K5IO8+d3IS+PiuCLo0CeDlP45yKsMxv0NKIpunTgdRj0HmCbhrsTQMeQuQnJzs6uvrq5s+fXrOs88+mxEbG2vSHUbdunW1Wq1WKCkpEQBSUlJc77vvvmZRUVFJnp6e2pUrV159bpWenu4cEBCgcXd3d8zAJtcd26K9yayITmX0gN643fMz5JyBtU9ZVd7oWuS+2uweWod548LZk3SZT7daXiLsem6pq+LyQmkukJMLTF6mSIaZHJ7p+WVM/+UwIbW9afP4IoR6baXMzdwUGQzl3+fuLs7Mv7czXm4uPLE0hoIyeUYVbqljE2Dv55C4AYa9Ay0GyfOZNYCYmBjPjh07tgkLC2v7/vvvN5g9e3aaqe/t27dv/pYtW3wKCwudxowZ0/z9999P7dy5c9msWbPS5s6de3XsfuPGjX6DBg3Kt9RR8cCWn2+x21Wik3N4+88EhrQN4rnBraBZHymB4PgqOPCtDJawfr35JbyMcVdkCJMiQ/hqRxI7Em/orGARSngqgdWeogjrn5MuYO5crLf6uRxY61mu0TLtlxhKKjR8O6ULfn614O6fQdRJE8grS+3uqI8gPw++ntyJlJwSXlwRJ0syyS1zbAKc2yUVb283TuoecQsxYcKEglOnTp04efLkifj4+IS+ffuWAJSUlBxp3bp1xenTp4//u+xbb72V8cknn1wd837mmWcyFy1aFOjr66uLjY09OW7cuAKQnrXFxsZenS7w22+/1X7yySerzqExA4fPiswrqeCZZbEE1/Lk47si/iuT1fMZaDUCtsyECwet9hw61Gg9Z4uYM6YdbRr48dzyWC7mWX+SU8pTbqz2PLxEam3U/1XpQkYhrPV8d8NJjpzP4+M7I2gVdCVpoHYojF8o1Qn880W7Oxqie2gdXh0RxpYTGSzYecbqz7tljs3CdPjjIajdXMrYVstkmUyvXr1K+/fvX2Bsgvbo0aPzIiIiLKjuIaF4YLNmHpsoiryy8iiZhWV8eU8n/K6dq+bkBOMWgF8w/D7VaGkjY+zdu9eq9xvCw1Ua9tFoRab/cpgKjXV1+5TylBurPDOOS5XQQ/vLmgGpD2s8/zqZwaK9yTzYqykjwq9LGmg1FPq+JJX8il9pN0djPNy7GSM7NODjLaesLuh9SxybOi388TBUFMGkpTd1Wr9SPPvss5eNTdB+8sknL1uzDsUDm6en5X2hlu5PYfPxDF4ZHkZEiJ5ndZ4BUkuRokxY94xVz9vCw8Mtfq8xmgV6Sx0BLuTx6Tbrnrcp6SknFnuWF8GKB6QGn+O/lz1Z5Hos9cwsKOPF34/SpoEfM0YYqCTU7xWp0em656SmpzZ2NAVBEHhnXDj1/Tx4ZlksReWGr6SNcdMfmwB7PoOU3dL0jnpt5JNSkRXFA1tFRYXxhfSQkFbA238mMKB1XR7qVU3qdMOOMHCmVI0i7jcLLSE5Odni95rCiPAG3N01hG92nuFQsuV3l0p7yoXFnltnweUkmLAQfOrJ6qQPSzx1OpEXfo+jpELDF3d3xN3FQPB1doEJ30vP26Iel672beRoDv6ernw6qSOpuSW8ufa48TcY4KY/Ni8dgR3vSM/VIu6W1UlFXhQPbNXdchqiXKPlueWx+Hu68tGdEcbbz/R8Gpr0gg0vS7X7LCAwMNCi95nD63e0JSTAi+eWx1JoYSaaLTzlwCLP01sh+kfo+SQ06yu/lB4s8fxxzzl2nc5m1h1taRlkZCgqoKnUh+v8XqlvnI0czaVbs9r8b0AL/ohJtXh+2019bFaUSKn93vWkuzX1uZpDo3hg0+nMf6b0xfbTnEwv5L3x4dTxMaGyiJMzjPtGOtgsvDIuK1O+G7aPuwufTorgUl4pc9adsOgzbOEpB2Z7luRIvdXqtoEBrysjpQdzPU9nFPLBpkSGtA1isqnV+iMmQfidUqeKi4cVd7SUpwe1JCKkFq9FHSMt3/xEp5v22ATYOhuyT0nP9b0srs2rYiMUD2zmphEfOZ/Lgr/PcGeXRgxqE2T6G2s1hts/hAv7Yc/nZlqCNS0SzKFLk9pM7y9dGW+KN3n6x1Vs5WktZntueBFKsmH8t1KxaxthjqdGq+PF3+Pw8XDh3fHh5nW/vv0jqcP3mv+BxrxkL1vtc1dnJz6b1JEKrY7Xoo6Z/d29aY/NpO1w6HvoMV1KaFJxeBxqKLKsUssLv8dR38+DWaPamr+yDpOgzWipOWmWeUkaAQEB5q/PQp4e1JJ2Df14fXU8ucXmPYO0pac1mOUZHyVlDvafAQ0ilJPSgzme3+06S1xqPm+NaUegKSMJ1+JZC0Z9LlWp+OdDxRytpVmgNy8NC2NHYhZRh81rwXRTHpvlhVJiWmArGPSGclIqsuJQySMfbU7kbFYxH0yMqJrabyqCIF0Zu3pKV8ZmDEmmptqmAzaAm4sTH06MIK+kkrl/mjckaUtPazDZs/iydLcW3AV6PaeslB5M9TydUchnW08zon19Rl6f2m8qrYZKzXN3fQKXYmV3lIupPZvSpUkAc9YdJ7PA9GG7m+7YBKmjSH4qjPnapiMJKtaheGDz8DDtYIi7kMePe84xuXtjere04iG0bxCMeB9SD8LB70x+W1iY0eavstK2oR/T+jcn6vBFs6qS2NrTUkz23PwqlBXA6K+kLEIbY4rntUOQc8e2N28I8nqGzZOyPVdPlzqBy+QoJ85OAh9M7EC5Rsdrq+JNHpK86Y7N5D1waCH0mAYh3ZSVusVQupO24oGtuLjY6DKVWh0zoo4R6ONueE6QOXSYBC2GSCVvcs6Z9JZDhw5Zv14zeXJgC1rW82Fm1DGTsyTt4WkJJnme3gZHl0Of5yHIgqFnGTDFc8m+FOJS85kz2oIhyOvxDLgyJHkcdpuWJWmPfd68rg8vDG3FtoQM1saZliV5Ux2bFSWw9kkpq3Wg7ZKZbhWU7qQtKNFw8FoiIyPF6Ojoapf5ducZ3t14kgX3dr6xgoOl5KfC1z0guBPcv9Zoeq5Op8PJSfE4fwOHz+cyYcFe7u3emLfHGp84ai9PczHqWV4I828DVy94Yhe4yNNXz1yMeWYWlDHw4510aRLAoge7Wne3di1/PCzNvZy2DwJbWOWoFFqdyPj5e0jNLWX7C/2o5eVW7fI3zbEJsGUW7P0CHlhns6kn1yMIQowoipHX/i4uLi45IiIiG4DV/wsh84S8DR/rtS1h7NdG+7x99dVXdb744osgQRBo06ZN6erVq8+9+eabQb/88ksgwJQpU7Jmz56daajbdqdOncKWLVt29t+mo4Y6ae/bt89zxowZwTt37kzS5xEXFxcYERHR9Prf271tzYWcEj7ddorBbYIY3r6+fCv2bwRD3oRz/8DRFUYXX7t2rXzrNoPOjQN4qFczft5/npgU4xO37eVpLkY9t7915dnFV3YLamDcc96GBCq0OuaMbidfUAOpIryLJ6x/1mjFHHvtc2cngXfGh5NXWsn7m04aXf6mOTYzTsC+r6Hz/XYLao5MdHS0x0cffdRg586dpxITE098++2353ft2uX166+/1omJiUmIjo5OWLJkSd09e/Z46uu2bYtO2na9YxNFkQd+OkRMcg5bn+9Hw1qWl9/Si04HPwyRJm0/FS0NAzkgxeUaBn+yE39PV9Y/1RsXZ8e/6rWKi4fh+4HQ7VFpioaDsjcpm8kLD/D0oJY8P6SV/CuI/lHqYDD2G+h4j/yfLxNvrz/Bwt3n+OOJ24hsepPP4RJFWDRSyl596rBd56wZvWOzE/PmzauXnp7u+uWXX15Nm507d269y5cvu3z22WeXAJ555pmGdevW1YwePTp/xIgRrUaPHp3zb7ft5ORk1wEDBrQ6d+5clTI3Xbt2bV1SUuK0e/fuxGubjtarV69DYmJivL5O2g55x7Y27hL/nMrixWGt5Q9qIBVKvuNTKM2FbXOqXXTVqlXyr99EvN1deGNUO06mF7Job3K1y9rT0xwMeup08OcLUgKFAzy7MORZodExa008IbU9md6/uTIr7zxVqiW5ZWa1Rbztvc+fG9KKhv4ezFwVT6XWcMEFe3uaSrWeR1dAyh4Y/KY6EdsAoigiCIJ4/e/0oa/bti06adut0WheSQVvrTtBRCN/7r+tqXICDTpIWU0xP1Xb3mbcuHHKOZjAsHZBDAqrxydbT3GpmvY29vY0FYOeR5bApcMw9G2p0LGdMeT5w+5znMkqZs7odni4KlSI2ckJRn0GZflSjUwzHW2Ft7sLb45uR2JGIQt3GU7GsrenqRj0LMuHLa9LU0863W9bqRrE8OHDC9auXVs7PT3dGSAjI8N54MCBRRs2bKhVWFjoVFBQ4LRhw4aAAQMGFOrrtm2LTtp2u2N7Z0MCeaWVvDu+A87GakFaS/8ZUnub9c+BVn966erVq5V1MIIgCLw5uh06UWTOOsOFaO3taSp6PUtypHlBTXpJJaYcAH2eF/NK+WL7aYa0DWJgmBnVbywhqB3c9iQc+VlKLzfR0dYMbVefIW2D+Hz7KS7klOhdxhE8TcGg5453oDhLqu1ZA5Jg7EVkZGTZCy+8kNanT5+w1q1bt50+fXpI7969SyZPnny5c+fObbp06dJmypQpWb169So11G1b6U7adnnGFpOSw4QF+3i8byiv3m6j1g8J66SOxkPnSUV2r8NRMrrm/53EB5sS+eGBSL0lxRzF0xh6Pdc9A4eXwhO77Zbefz36PJ9YGsPfpzLZ9nw/GgXIm3Sml4oSmN9dSiZ5Yje4VM0+dJR9fimvlMGf7KR7s9r8OPXGDFFH8TSGXs/0Y/BtX4h8SApsDoCjPmOTgz179nh++OGH9VevXl3tfKyhQ4c2//DDD1MNNR212zO2goKCKv+v1YnMWn2c+n4ePD2opdKr/4+wO6DVcOmqLP/GygN//fWX7Vyq4ZHeobSs58PsNccprbixcoqjeBrjBs/UGIhZLA0LO0hQgxs9/07MZNPxdJ4a2NI2QQ3AzUuqGJ+dCHtvrHPqKPu8YS1Pnh/Sih2JWWyMT7/hdUfxNMYNnjqd1OncM8AhnvveCijdSVvxwObtXTVT85cDKZxIK+D1O9rg7W7DShOCACM+kHpjbXzlhpe7du1qO5dqcHNx4u2x7aXhsL9O3/C6o3gao4qnTgsbXpCKAPe7cdvbk2s9yyq1vLH2OKGB3jzSp5oegErQcgi0HQP/fAy5KQYd7c3Unk1p28CPt9aduKEpqSN5VscNnnG/ScXTh7zlsJnTNyNKdtJWPLBd2yIiu6icjzYn0rN5Hcvr7VlDQBPo/wqcXA+ntlR56eRJ4/N0bEX30DpM7NKI7/85y+mMwiqvOZJndVTxPLxYatI4bB54+Bl+kx241vPbnWdJuVzCW2PaG24eqiTD3gXBCTbNqPJrR9rnLs5OzB3bnvSCMj6/rhu8I3lWRxXP0lypJU1Id4iYbD8pFVlRPLC5uf33vOD9jScpqdDy1hiZJ7uaQ4//SZW6N74Elf8F3UaNGtnHxwCvjgjDy82ZN9Yer5JK62iehrjqWXxZmmrRtA+0n2BfKT3863n+cgnz/05iZIcG1tUqtQb/YOnCK3EDJG68wdFR6NIkgEmRIfy4J5nE9P8uvBzN0xBVPP96G0pzpOLpNeD5IKDT6XRql1PgynbQO/9E8T357xhqTEouv8ek8nDvZrSoZ6TrsJK4uEkHcW4y7Pns6q9zc3Pt56SHOj7uvDQ8jL1nLrP+6H992xzN0xBXPbe/CRVF0kRsB+w6nJubiyiKvLnuOC5OArNG2vn5X4/pUDcMNr4sJZXgmPv8lRFh+Hq4MGv1f0WSHdFTH1c9Lx2BQz9At8ekaUE1g/isrCz/Wz246XQ6ISsryx+I1/e64g+5BEFAqxOZvSae+n4ePGXLhBFDhPaT7h52fQId7oLaobi6WtAmR2Emd2sk6A13AAAgAElEQVTM8kPnefvPEwwIq4ePu4tDeurD1dUVLhyCw0ug51NQz0bZr2bi6urK1hMZ/HUyk5m3t6G+v51bkzi7Shdei++QiiQPfN0h93ltbzdeGR7Gq1HHiDp8kQldGjmkpz5cXV3/SxjxrgsDXrO3ksloNJpH0tPTF6anp7fHBjcmDowOiNdoNI/oe1HxwObk5MSvB1I4fqmAL+/phI8tE0aqY+g8OLVZSiSZvMLk9jq2xNlJYO6Y9oybv5cvtp/mtdvbOKSnPjzcXOHP58G3gcMljFTB2Y05q07QKsiHqb2a2ttGolkfqUPFns8h4h6H3eeTIkNYfugC725MYHDbIIf1vB4PDw84shQuRsO47xyiUICpdOnSJRMYbW8PR8fiiC8IwpuCIDwjCMJ91S1XXlHJh1cSRu7oYIeEEUP4NYD+r8LpLZC4gexsx5wa0qnxlecZu89xKqPQYT2vRzi8CNKPSgkj7nYcejbCt7tTuJhXytwx7XF1pBqdQ+aCiwdseJHsrCx72+jFyUng7bHtySmu4OMtiTXm2My9dOa/QgEd7rK3jooCWPRNFgShM1AqiuLnQH9BEAz2s8irwP4JI4bo/jjUawsbZ9A0WOEKE1bw8vDWeLu7MHtNPE2aNLG3jnGKsmh06iepMnq78fa2MciZrCLWniphfKdguofWsbdOVXyDpDlVZ/6ilSbB3jYGaR/sz5QeTVi6P4VSDzsl3ZhJWOoKqXzW7R855HNfFeux9BJ1BPBv/Z8kwGB72bxSjf0TRgzh7CpVGcg/T9GGN+xtY5A6Pu68NKw1+8/msHBLrL11jLPtTagodugThyiKvLHmOK5Oou2q35hL5MNQPxy3v96Q+tc5KM8PbU0db3dmrz2BTqdsJSOrSY3B/fgyhysUcD1rYi8aX0jFIJYGtobAv+MjOUCVMUZBEB4TBCFaEIRoJ0THSBgxRJOe0OFuGqeugWy9vewcgnu6NSY82J+oc6LJ3bbtwvkDEPszYvfpULe1vW0M8uexNHYnZfPSsDDq+tqvH1y1OLvAyE9wr7gMO9+3t41B/D1dmTkyjLP5OpYdMtqj0n7otNJzX58gqX6sg3K5qJxZq/Um+6mYiBwPFQTg+hYG34miGCmKYmR9L8FxEkYMMXQuGsEVNrxotOmjvXB2Epg7tj1ZheV8vu3GiiQOgVYjVRjxC2ZLeUd72xikqFzD3PUnaB/sR2Ce4w7zARDSjfOB/WH/Ash0XNexHYNp4Sfy/qaTXC4yuwKSbYhZBGmxHKk30aGf+364OZESPeX0VEzH0sB2Cfh3QL02kGZowToBNSDjyKcerkPnwNkdcMJxK5R3DKnF3d0a89PeqhNjHYboH6VissPeYcSYifa2Mcjn206RWVjO3DHtGT3qDnvrGKXxgz9KJ+I/X3DYCy9BEJj/cD+KyzUmddu2OcXZUtf2Zn3pPOVte9sYJPZCHsujL/Cgo2To1lAsDWybgJ5Xfm4BGGx0Vl2jUUdiVWoA1A+HTa9BeZG9dQzSpjJJmhi7Jt5gcz+7UJQpVXEIHQBtxxAVFWVvI70kphfy455k7u4aQqfGAQ7reS1Rm3dKjS9T9sDR5fbWMUj8nq083LsZK6JTiUkx3DjVLmx74+pz3ygHbYj673zfuj7uti0QfxNicdsaQRBmAwXAZVEUlxpaTl/bGoflwkH4YQj0fBqGzrW3jUF+PXCe11Yd47NJHRnbKdjeOhKrpsGx32H6Pgh0zC+lKIpM+m4/pzMK+euF/gR4G0zmdTx0OunYzEuBJ6PBU38DX3tTXK5h8Cc7qeXlxrone+HiCFMozh+AH4dCr2dhyBx72xjkt4PneTXqv++1vrY1KqZh8VEniuJboih+Vl1Qg5pzxxYVFQUh3aDTFNg/32GfZ0RFRTGpawgRjfyZtyHBMRJJUvZB3K9ShZErQc0R74RWHbnIwXM5vDI87GpQc0TP64mKipLqGI78GEouw4559lbSS1RUFN7uLsy6oy0JaQUs2Zdi/E1Kc81zX/q+BDjmPs8rqeCDTSfp1qw2Yzo2NP4GlWqxS6NRh6Y4G77sAkHtYep6h01Xj7uQx9j5e3ioVzNm3WHHtGWtBr7rB6V58ORBcPM2/h47kF9ayaCP/yakthcrn+iJk9Jd25Viw0twaCE8ugMaOmaCjiiKPPDTIQ6n5PLXC/2o52fHiiQHvpXqbt65GNqNtZ+HEWauOsayQxdY/1Rv2jSQOmCod2yWY/NGo47Kpk2bpB+8A2HwG5CyG479YV8pPfzrGRFSi7u7NmbR3mROpttxGx/6HjLiYfi7VYLa1e3pIHy8JZGc4grmjmlfJag5mqc+qjgOmAlegVIiiU5vYXO78a+nIAjMGd2OCo2OeRvsOPLx73Pf5gOlXndXcLR9Hn8xn18PnmdKjyZXg5qKdSge2Hx8fJRehSz06dPnv//p/AA07AxbZkoVChyIaz1fHtYaXw8XZq8+bp9EkoJL8Nc8aDEY2oyq8lKV7Wln4i/m8/P+FKb0aEL74KpZuo7kaYgqjp61pOe/F6PhyBL7SenhWs9mgd480S+UNbGX2Jtkp1JbW2aBpgxGVO0s4Uj7XKcTmbUmnjrebjw3pJW9dW4aFA9sJSUlSq9CFmJjr6no4eQsPc8oyoQd79pPSg/XegZcqbB+MDmH1faoVLDpVdBV6m1JU2V72hGdTuT11fHU9nbn+aE3Thh3FM/quMGxwySpzuG2N6V+dw7C9Z7TB7QgpLYns9bEU6Gx8d3luX/g6DIpESywRZWXHGmf/3boPEfO5/HqiDb4e9aM7gg1AcUDm7u7g1Z1uI4WLaoe/AR3hsgH4eC30twsB+F6z0mRIUSE1GLenycpsGUiSdI2ac5fnxegdugNL9+wPe3ErwfPE3shj9duD9N74nAUz+q4wVEQpHJlZQVSvzsH4XpPD1dn5oxux5msYn7Yfc52IppyWP88BDSFvi/e8LKj7POswnLe33iS20LrML6zg2Q33yQoHtgqKx0ga88E0tL0zDEfOAs8A6S+TQ7yPON6Tycngblj2nG5uJxPt56yjURlqbRN6rSAXs/oXUTv9rQxmQVlvL/pJD2b12GcgWkRjuBpDL2OQW2leoeHl0h97xwAfZ4Dw4IY0jaIL7af5mJeqW1E9nwOl09Loy6unje87Cj7fN6fJyir1PH2uPaOVyC+hqN4YHN2dlZ6FbLg66unxI5XbRg8By7sh7jfbC+lB32eHRrVYnK3xizem8yJSzZIJNn9KeSeg5GfgIv+O3K929PGvLX+BOUaHW+PNXzicARPYxh07D8DfBtK9Q+1GttK6cGQ5xuj2iIi8ta648pLXD4D/3wkdZVoMVjvIo6wz/ckZbM69hJP9Auled2akYdQk3CA2ZMOTsd7oVE32DobSnPtbWOQl4a1xt/TldlKVyTJTpICW/idUidyB2VHYibrj6bx5IAWhN6sJw53Xxj+jtT3LvoHe9sYpFGAF08NbMnm4xnsSMxUbkWiKAV5F3cpS9dBKavU8vrqeJrU8WL6AMcYFr3ZUDywabU1o5hnYaGB2ov/TowtzZFSh+2MIc9aXm7MGBFGdEouf8SkKrPyqycOT6kDeTUY3J42oLRCy6zV8TSv683j/W58/nct9vQ0lWod246Vypj99TYUZthOSg/VeT7aJ5TQut68seY4ZZUKnRPiV8LZv2HQbPCtb3Axe+/zb3ae4Vx2MXPHtMfDtWaMaNU0FA9srq41I9OnQYNquns36ABdH4VDP8ClI7aT0qdSjeedXULo0iSAeRsSyFaiwvqxP+DcThg0S2qEWQ3Vbk+F+Xz7aVJzS3lnXDjuLtWfOOzpaSrVOv6bSKIpg62zbCelh+o83VycmDumPedzSljw9xn5V16aJ2XpNuwMkQ9Vu6g99/nZrCLm7zjDqIiG9G1V124eNzuKB7bycgdtYXEdSUlGerENnAneda9MjLXfXWh1nk5OAu+ND6ekXMucdSfkXXFxNmx6BYK7GD1xgAnbUyFOphewcNdZ7opsZFJXbHt5moNRx8AWUlr70eWQvNs2Unow5tmrRSCjIhqyYOcZUi4Xy7vy7XOgJBtGfSZN16kGe+1zUZSmnri7OjHrDgdtbnuToHhg8/LyUnoVstCxo5HyRB7+MGweXIyBg9/ZRkoPxjxbBvnyvwEtWBd3ie0JMg5NbZohpZeP+droiQNM2J4KoNOJvBZ1DD9PV14dYdqJwx6e5mKSY58XoFZjKVtVa59MZFM8Xx/ZBjdnJ2avkbGoQPJuqWVS92nQIMLo4vba58sPXWDvmcu8MjyMer52LDN2C6B4YCsqctwWMNeya9cu4wuF3wkth8K2OZBzVnkpPZjiOa1/c1oF+fD66nh5iiQnbpIq9/d9CeqZFjBM2p4ys2hvMofP5/H6yDYmV+63h6e5mOTo5gUjPoCsBNjzmfJSejDFM8jPg2cHt2TnqSw2HEu3fqUVJbDmSWnO2sCZJr3FHvs8Lb+UeX8m0CO0NpO7Nbb5+m811CLI5pJ/Eeb3kK4M718rJZc4IIfP5zJhwV7u696EuWPbW/5BZfnwdQ+plNNjO8HFMVu9nMsuZsTn/9CzeSA/PBB5684L+n0qJKyHx3dCUDt72+hFo9Uxdv4e0vLK2PJcX+r4WFHEYdNrsP9reGA9NHOcUlnXIooiDy06xL6zl9n8bF+a1DGtULhaBNlyFD8r16i2NabgHywNSSbvgpgflZXSg6menRsH8GDPZizdn8Iea2r1bZ0NRekw5iuzgpotW4PodCIv/xGHm7MT744PNyuoOWILk+sxy/H2j6Rh89XTbD4kaaqni7MTH9/ZkYKySmavsWJu2/kDUoupyIfNCmq23uerYy+yIzGLl4aFmRzUVKxDvWOzBFGEpeMg9ZDUWLOWYw4tlFZoGfnFLsoqtWx6ri9+HmZmqJ7eCr9MdPjGqz/sPsfc9Sf4+M4IJnRpZG8d+3NiDay4X+oE0O9le9sY5OsdSXy4OZGvJnfijg5m9iCrLINvekvZoNP3SXP6HJDMwjKGfvoPoYHe/P5ET5zNaJek3rFZjnrHdgWzruIEAUZ/If28appNsyTN8fR0c+aTSR3JKCxnzlozsyRLcmDN/6BeW+kEaSa2uio+l13Mh5tPMjCsnkX19m66OzaQWrS0nwA7P4D0eGWk9GCu5+N9Q4kIqcWs1fFkFZqZPb3tTals1qjPzQ5qttrnoijy0u9HKa3Q8sHECLOCmop1qHds1nDkF1gzHQa/Cb2fs7eNQT7eksiXfyXx3ZQuDG1neOLqVURRuuJP3AiP7YD64cpLWkClVsfEBXs5l13Mluf6Ud9fzTS7SkkOfN1dmqLy6F/g6pjbJimzkNu/2E3flnX5/v4upg0jJ22Hn8dDt8ekzhIOypJ9ycxec5y3xrTj/tuamv1+9Y7NchS/Y8vPd6x+ZoZYv369+W/qOFm6Ov5rHlyyTSsMSzyfGtiSdg39eDXqmGlXxkeXQ8JaKcvMwqBm0fY0k0+3niIuNZ/3JnSwOKjZwtNaLHL0qi09F808Lj0ntQGWeLao58vLw1qzLSGDn/enGH9D8WXp+WHdMBjylgWWttnnpzMKmfdnAv1b12VKjyaKr0+lKorfsXXp0kWMiYlRdB1yUFFRgZubBRl/JTmwoJfUPfrxf6S0awWx1DMxvZDRX+2mW7PaLH6wW5Uu0lXITYZv+kgZdVP/NGnOmpyeprL3TDb3LjzApMgQ3pvQweLPUdpTDqxy3DgDDiyAySug1TB5xa7DUk+dTuShxYfYe+Yya5/sRVh9A12kRRGW3went0h3oRZedCm9zys0OsZ+vYf0gjI2PdvH4jlr6h2b5ajz2K6wd+9ey97oVRvGLZDG+ze/Jq+UHiz1bF3flzdGtWPX6WwW7DRQ0khTLqWLI8C4bywOatZ4mkJucQXPL4+jWR1vZo9qa9VnKekpF1Y5DpkDQeHSXU6hDPPGqsFSTycngY/ujMDPw5Wnfj1CaYWBZ9aHF8PJ9VItSCuGx5Xe5x9uPsmJtALeGx+uTsS2E4oHNk/PG/shOSLh4VY8RwrtL/Uli/kJjq6QS0kv1nje0y2EUREN+WTrKQ4l59y4wJbXpVqYY+dLE16twKrtWQ06ncjLK49yubicL+7phJebi1Wfp5SnnFjl6OIOE3+QJjKvelzRRCdrPAN93Pl0UgSnM4uY+6eeRKdLsbDhZangc4//WWGp7D7fFJ/G97vOMaVHE9OeZ6soguKBraKiQulVyEJycrJ1HzBwNjTpBWufhgzl+k5Z4ykIAu+Ma09IgCdP/XqEnOJr9k18lFQq7LYnoc0ddvWsjgU7z7D1RAYzRrShfbC/1Z+nlKecWO1YtzWMeF+qfL/jHTmU9GKtZ5+WdXm8Xyi/HjjPqiPXdKgoyYEVU6REmAkLrS6KoNQ+P5tVxIu/HyUipBavq7Ug7Yrigc3FxboralsRGBho3Qc4u8DEn6TJscvvkyp2KIC1nr4ernw1uTM5xRU8s+wIGq1Oas649mmp79zgNx3CUx9/J2by0ZZExnRsyEO9msrymUp4yo0sjp3vh05TYNdHcGKt9Z+nBzk8Xxzamu7NajNj5TGOpeZLneujHoOCNLhrMXhbvw4l9nlJhYZpPx/G1Vlg/r2djXaVUFEWxQObTqdTehWyUFZWZv2H+AbBnYsg7/yV+W3y/+1yeLYP9uftse3ZdTqbj9YchN/uBmdXuPMn6b8yIMv2vIaUy8U8/dsRWgf58t74DrKVzJLbUwlkcRQEqa9gcCSsegIyE6z/zOuQw9PV2Yn593Ym0Medx5dGU7ztHUjaCiPeg0by5FHIvc9FUWTmqnhOZRby2d2dCK5VMx6/3MwoHtiUzrqUi8pKmcoPNbkNhr4NiX/CX/JX65DL866uITzaM4TeR55He/ksTFoK/vJV7ZBtewLF5RoeXxqDIAh8NyUSTzf5robl9FQK2Rxd3KX97O4DyyZLPcxkRC7POj7ufDulC91Kd+K990N04ZOkslkyIfc+//KvJFYduchzg1vRT+2x5hCoQ5FXCAgIkO/Duj8BXabC7k+kdhoyIpunKPIqC+ntfJwZlY+wXyfvMwG5PCs0Op74OYbTmUV8cU8nGteRdzqFrPtdIWR19GsIdy2BvAuw7F6pNJVMyOnZXnOcj13mc1DXmte1jyDn5bGcnlGHU/lk6ynGdwrmqYEtZPtcFetQk0eukJqaanwhUxEEuP1jaDlMakyauEm2j5bNc99XOB1eTPltz3I4YASPL43hZHqBPJ+NPJ46ncgrK4+y63Q274xrr8jVsKz7XSFkd2zcA8YugJTdEPWIbJmSsnlmJcJv9+Ac0JToHl/z6+Es3t+UKM9nI5/n3jPZvLLyKLeF1uG9CfINj6tYj+KBzcOjZszjCAsLk/cDnV1g4o9QvwP88SCkyjNJXRbPmEVSan/bMbgPeYNFD3bD09WZ+xYe5GyWPPMO5fB8b9NJVh25yItDWzGpqzKFpmXf7wqgiGOHO2H4e5CwDv58Xpr8bCWyeBamS4W3nV3hvj+YNiKSKT2a8M3OM3z/jzw9EOXwPHGpgMeXxtC0jjffTOmCm4tjtq+6VVF8bxQXy9wCXiEOHTok/4e6+0gVH7zrSt0ALli/Dqs9Dy+Fdc9IDVPHfw9OToTU9uLnR7ojiiL3LjzAhZwSu3t+vSOJ7/45y/23NeF/A5Qb4lFkv8uMYo49pkHv56ULne1vWR3crPbMvwg/3S6VzZq8AgKaIggCb45uxx0dGjBvQwIroi9Ytw4ZPOMv5jN54X583F346cGu+HvKk3ClIh9qEeQr6HQ6nJRqGpp3ARaPguIsuPcPKcHEQqzyjP1NqkDRfADc/dsNhXFPXCrgnu/34+/pyrLHetDQiuwuSz1FUeT9TYl8s/MMYzo25JO7OipaFV3R/S4TijqKIqx/Vgpu3Z+AYe9aPE/MKs+881e+I5fhvj+k4dJrqNDoeHjxIXYnZfPW6HZMsaCosByeR1PzuG/hAXw9XPnt0R6yP/O9FrWkluWobWuusHatMnN7AKgVAg9uAN8GUlXyc/9Y/FEWe0b/JAW1Zn3h7l/1Vntv29CPxQ91I7e4gokL9pKUafmwpCWeOp3IrDXxfLPzDJO7N1Y8qIHC+10mFHUUBBj5KfSYDge+kbpVaDUWfZTFnjnnpDu10ly4f80NQQ3AzcWJ7++PZFBYELPWHOfTracszri21PPI+VzuXXgAvysXfkoGNRXrUO/YbElhBiwZLX2Rx3wFHe5Sfp06HeyYJ03MbTFEyogzUqg5/mI+U386iFYnsuC+LvQIraO4Zlmllpf/OMrauEs83i+UGcPD1IfxtkQU4Z+PYMfb0Pp2qcKHmw26PV84JE090FXClNXQsGO1i2u0Ol6NOsbvMancf1sT3hjVziZ9zjbFp/Hs8ljq+Xrw66PdaRSgfFBT79gsR71ju8KqVauUX4lvEDy4ERp1hahHpXYiWvPm1JjlWZYvnTR2fSRVnrhnmUndB9oH+7NyWk/q+Lhz38IDLN6bbPbVsTmel/JKuevbfayNu8TLw1vz6og2NgtqNtnvVmITR0GAfi/BiA+lPnw/DIUc85I1zPIURel576KR0jH50GajQQ3AxdmJDyZ24PG+oSzZl8LUnw5WLQ0ns6dWJ/Lp1lNM++UwbRr4sXJaT5sENRXrUO/Y7IGmAja+LBVNDukO476F2s3kXUfKXqnobcEl6blJt0elk5cZFJRV8uyyWP46mcmwdkG8N74DAd7ytvvYeCyNGVHH0Gh1fDqpo1o41hFI2gZ/PAyiTmrk2WGS2cdOtZTmScf/0eXS0Pidi6UuGWay7OB5Zq89Th1vNz6cGEHvlvKWyrqYV8pLv8ex98xlJnRuxLxx7fFwtV2pLPWOzXLUO7YrrF692nYrc3GDUZ/BhB8g4wQs6Al7v5QCnhGMepbmwp8vSs8sBCfpDrH7YxadmPw8XFl4fyQzb2/D9oRMBn2yk1VHUtHpjF8MGfNMyy9l2s8xTPvlME3reLH+6T52CWo23e8WYnPHFoOl3oJB7aSLo9/ulobPjWDUUxTh+Gqps/exP6D/a9LwowVBDeDubo1Z+URPPN2cue+HA7wadZTLRcYb6Rrz1Gh1LN6bzLBP/yH2Qh4fTOjAx3dF2DSoqViHRXdsgiBMEkVxuSnL1pQ7Nrtlx+VfhPXPwenNENAM+s+AduOl4KcHg57lhXDweylAluVB10ekvlXuvrJonkwvYMbKY8ReyCM82J/nh0jlgww1LDXkmVVYzve7zrJkXzKiCE8PasljfUNxdbZPZuItnxVZ7Yq1sH8+7HgXdBqpmk7vZ6XqJfoWN+QpinB2h/Q5qQel/nBjvoSGnWTRLKvU8vGWRH7ak4ynmzOP9A5las+m+HvpT8M35KnR6tgQn84X20+TlFlE7xaBvDs+nJDa9hl6VO/YLMfswCYIwihguiiKI0xZvlWrVuKpU6cscbMp27ZtY/DgwfZZuShC0nbpmVvmcSl7ssMkaDsGGkRUafhZxVNTDil7pKvg+JVQUSQliAyaDQ0s7yptCK1OZE3sRT7ecoqLeaWEBnozvnMww9vXp3ldnyrPxa71LC7XsOt0NuuPXmLz8XS0OpGxHYN5bkgru5009Hk6KnZ3LLgkJSDF/ibd+bcaDuF3QvOB4PFft+sqnqIodY04uR7ilkFWgnRc938VOt4rFTCQmdMZhby/KZFtCRl4ujozskMDRkU0pHuz2lXutq711OlEEtIL2HgsnVVHLnIxr5Tmdb2ZMaINg9vUs2sCkxrYLMfSO7ZFoihONWXZTp06iUeOHDF7HbYmPz8ff3/r+3tZhU4HZ7ZLfdHO/CVdJbv7QVB7CGgC7r6UV1TgrimUHuxnJoCmDFw8of146PowBHdRXLNCo2NjfBpL9qUQk5ILQG1vN9o28KNhLQ88XZ0pK6+gsFLkbFYxpzOL0OpE/D1dmdC5Eff1aExoXR/FPU3BIfa7ERzGMTcZDv0Asb9AyWUQnCGwJQS2Au+6lGu0uAtayL8gHZtFGdL7giMh8iEInygVYlaYE5cKWLo/mXVxaRSVa3BzcaJVkA/NAn2o5emKprKCSpw5n1NCYnoh+aWVOAnQq0UgU3o0YXCbIIMjEbZEDWyWo0hgEwThMeAxgPr163dJS0uzWNBWHDhwgO7du9tb4z+KL0tBLmWvVDsvLwUqitFoNLj41QP/EKgfDk37SA/gTch2VIK0/FL+TswiJiWXpMwi0vJLKavUodVoCKrlRaMAL8KD/enZog5dm9a225CjIRxuv+vB4Ry1GmlI8cwOSD8GOWegOBtNZQUuHt5Sl4g6LaFxd+muzspu7JZSVqnlwLkc9iZlcyKtgPM5JeSXVlJZqcHPy53gWp60qOdDt2a16d0ykHq+jlX+Tw1sllNtYBMEYRgQcs2vToqiuNucO7aIiAgxLi7OOksbcPHiRYKDg+2tYRTVU15qgmdNcATVU27UwGY51V4+i6K4WRTFhdf8223uCjQay6oY2Jrc3Fx7K5iE6ikvNcGzJjiC6qniOCg+LlRTqke4utaMQqaqp7zUBM+a4Aiqp4rjYHZgEwRhDDBAEIShJq3AwVOp/6WmtNdRPeWlJnjWBEdQPVUcB8UrjwiCUAjI1yVQOQKBbHtLmIDqKS81wbMmOILqKTetRVGUZyLqLYb8k0luJLEmPAAVBCFa9ZQP1VM+aoIjqJ5yIwiC41e2cFBqxjihioqKioqKiaiBTUVFRUXlpsIWge07G6xDDlRPeVE95aMmOILqKTc1xdPhUDx5REVFRUVFxZaoQ5EqKioqKjcVamBTUVFRUbmpUAObioqKispNhRrYVFRUVFRuKhQLbIIghAiCsEMQhARBEI4LgvCMUusyw8lDEISDgiDEXXGaY+L7vhUEoZej/E2CILQQBCFLEIRkQRBiBUHIEQThjCAIfsbfbRuubNA8He8AACAASURBVLN+jrC99CEIwnBBEBIFQUgSBGGGvX2MYc/taeX3xm7HgKN8X1XsgCiKivwDGgCdr/zsC5wC2iq1PhOdBMDnys+uwAGghwnviwWcHelvAlYBfa78/DcQbs9ta2CbBTvK9rrOzRk4A4QCbkCcI3g56va08ntjt2PAkb6v6j/b/lOspJYoimlA2pWfCwVBSACCBUGoAPYBxUAe0BjIBTqJoliglM8VDxEouvK/rlf+iYIgtDDkhPTFPCWKovbK33PD3wSckNtVEIRtQH09L80URXEN0A6Iv/K7MGxcj9PEbXYRuAjKby8z6QYkiaJ4FkAQhGXAGOzo5cjb08rvjd2OAUc8B6nYBps8YxMEoSnSwX5AFMUkYDcwRRTFjsBRYKytDihBEJwFQYgFMoGtoigacxoBbKrub1LCUxTFwaIottfzb40gCJ6AhyiKuYIghACXRVGsUMKjGj+ztpnS28tMgoEL1/x/6pXf2Q1H355yfG/seQw40jlIRXmsCmyCIGwTBCFez78x1yzjA6wEnr3mwFHsbsOYkyiK2isHcyOgmyAI7Y04DePGL6i+v8mWtAUSrvzc5pqfbY1J28wBttf16GsS6AiVChx2e1r7vbHnMWDrc5CK/bFqKFIUxcHVvS4IgivSAfWLKIpRV36n6N2GMadrlssTBOFvYLggCGf0OQmC4AXUEkXxUnV/kx249ktZCnQWBCFMFMWTthIwtB+v32YOsr2uJxUIueb/GwGXDCxrE2rK9rTke2NPZ3ucg1Tsj5JZkQLwA5AgiuIn17xkt7sNQRDqCoJQ68rPnsBg4GQ1TgOAHde839DfZFNEUVwiiuILV37eJYpiqC2D2hWMbjNH2V56OAS0FAShmSAIbsDdwFo7Ozns9rTme2PPY8ARz0EqtkHJZ2y9gCnAQEFKSY8VBOF2DNxtKOhxLQ2AHYIgHEU6uW0VRXF9NU7XPycw9DfdipiyzRxye4miqAGeBDYjndRWiKJ43L5WDr09rfne2PMYcMRzkIoNUIsgV4MgCIeB7qIoVtrbpaagbjN5qYnbsyY6q9xc2CKwqZFTxWEZPnw4mzbdkPSqouII6EtyUjEBxdP9o6IcJV+gelRPeakpnklJSfZWMEpN2Zaqp4qjoN6xqdyULF++nEmTJhldLjIykujoaBsYqaiYjXrHZiGK37HVlGEe1VNe7Om5bt06Fi1aZNKyBQWOMK2uetR9Li81xVPFchS/Y9N+O0B09vQHv2Co2xqa9IQGHcFZsWpe1SKKImezi9l/9jIn0wo5n1NCcbmGSo2WWt7uNKzlSVh9X7o1q01YfV+kjGHHobi4GG9vb3trGMXenlOnTq0a3CpLIWUvXIyB7FNQmA7aCiLn7if6g7FQOxQadoamvcGrtt28C8oq2XfmMsdS8zmXXUxWUTkVlRrcXV0I8vOgaaA3nRvXomvT2ni72+c7ZAh773NTcThPUYSsREjeBZkJkJcC5YXw8BbHOvnUIBT/ZhRUQIBzESRthdifpV96BkD7idBlKtRvX+375SKzsIxlBy+w6shFzmUXA+Dr7kLjOl74e7pSVlxIDgKxF/L47eB5ABr4ezCuUzD3dGtMSG0vm3gaIzY2ll69etlbwygO4SmKcO4fiPkJTm2GyhJAoMC5FmezSinXCpRXVEDGCTi5AXSVIDhLwa3LAxA2ClzcFNes1OrYnpDBrwcvsDcpG41OxNlJoEltLwJ93dGUleDm4seRC7msP3oJnQjuLk4MaF2Pe7o3pm/LQIe4AHOIfW4CDuOZfxEOL4a43yBPOufg7g+1m4GHv33dajiK37FlZGSIQUFB0v8UZ0snmoR1kLgBNGXQcigMfB0aRCiy/szCMr7YfpoV0alUanX0aFaHkR0a0KtFIE3reF09IWRkZBAUFIQoilzKL2PP6Ww2xqex81QWgiAwJqIhzw5uReM69g1w/3o6Onb1FEU+mT6C5yOKIP0YeNaGduOg9e0Q0rXKSSMiIoK4uDioLIO0ODi1CY5HQW6yNMrQ72XoeC84u8quqdWJRB1O5Yu/TnMhp5SG/h6M6tiQQWFBdGjkj4erM1B1WxaVa4g9n8e2hAzWH00ju6iclvV8eHFYa4a2DbJrgFOPTRPJvwh/vwtxy0CngdD+0G4shA6AWo3hv31o/6uVGorigS02Nlbs2LHjjS+U5sKhhbBvvvRz5ykwZC541pJlvVqdyI+7z/HZtlOUa3TcGRnCY31DaRaofwgiNjYWfZ5p+aX8sOscvxw4j1YUebxvKP8b0OLqScfWGPJ0NOzmmXMO/nwBzmyHgKbQ9yVpdMDVQ+/ibdu25cSJ6wrN63TSCMM/H0LqIajXFkZ9DiHdZNOMu5DHzNXHiL9YQPtgP54a2JLBbYJwdrrxXGZoW1ZodKw/eomvdiRxNquY7s1q8874cJrX9ZHN0xzUY9MI2krY8xn88zGIOmlU4LYnIaCJoXeogc1CFA9sZ86cEZs3b254gdI82PkBHPgGfIJgzFfQYpBV60y5XMyzy2M5cj6PQWH1mDmyDaFGvuxnzpyhOs/0/DLe3ZjAmthLtAry4dNJHWnX0PbDBcY8HQWbe4qiNOS46TVwcuHntGbc99lfRu+0wsPDOXbsmOHPPPknbHwFClKh51MwcLZVw5OVWh1fbj/NVzuSCPRxZ+bINoyOaFjtnZaxbanR6lgefYH3N56krFLHKyPCeKhXU5vfvanHZjVknoSoRyH9KLQZDUPnShde1aMGNguxSduaavGsBcPfgUe2gYcf/DwBdrwDOq1FH7cpPp07vtjNmcwiPr+7IwsfiDQa1Eyhvr8Hn9/diZ+mdiWvpJJx8/ey4tAF429UUZ7y/7d33nFVVn8cf1+GgANxoOLEzXIg7pFabk3NypFppS21XVaW5Wj8bFhqVmZZWrnNHIgL916oCIKKiICigsje957fH0+SyAXueJ57L/a8Xy9eL+U+48M55z7f55zzHRmw9hkIfBMadmZ780/4cFMsO3btKfvc0tBowHsITDkG7SfA4e9gSV9IMa3fb6XnMGbxURbsjuIx//oEv92TYW3rmW2AHOztGNupEcFv9+ShFu58Enie55edJC1HTfxhE4SuhZ97Q9p1GPkHjPrDEKOmYgaKG7b09HTDDqzXDl7YA23GwL4vYPU4yMs06l4/74/m5T9P0aRWZba81sOoh4ahOnt71WLbGw/R0bM67/4VyoyNYWh1lgvVM7g9rYzFdKbEwq/9pX3bPrPg6fX0f/I5rl69Sr9+/co8Xas14AXKqTIM+RZG/Qm3L0sPqVjjSoqFXUvl0e8OEn49jfmj2zJ3ZBtcnQ3btzO0LWtVcebn8QHMfNSHfRcTeez7Q8QkGfcdMgd1bN6HTgfBM2H985In+MsHwWeoZe79H0dxw+bh4WH4wRUqwvAfYOCXcHErLB0MWcllnqbTCT4NPM9nQREMbuXB6hc7G+3FaIzO6pUqsGxCR57v3phlR67y8p+nyMk3bYZpLEa1pxWxiM6b4bCknzSDGrsWur8BdsYNaUdHI5xCvB+FF3aBUxX4fRhc3m3QaSdikhmz+CgOdnb8Nakrw9oaV9PUmLbUaDQ8260xfz7fieTMPB7/8TARCZaJ1VPH5j1o8yWDdvBbCHgOntkEruWjfR4EFDdsRqcs0mig00sweoXkhr1sKGTeLvHwvAIdb6w+wy8Hr/BsV0++G+NvkmOHsTrt7TRMH+LDrKG+BEfc5MU/LGPcykMKKLCAzmsh8OtA6d8TtkEzg8rwFSM3N9e4E9xbwoQdUKMprBgl7cGVwr6LiYxbcgz3Kk6sfbkLPnVdjdZoSlt2blKDdZO64mhvx5ifjxIan2L0NYxFHZv/oM2HdRMg7C/oM1Oa7SvgVatSMoo7j2RmZgqTgyGjdsGqp6BGMxi/CSrVKPKxVid4dWUIQedu8N4AL17u2cTk/QpzgjbXnIjjvfWhPNTcnZ/GBSjqMWlzwaUloKjOG2HSbN7JFZ7bIrlIm0i7du0ICQkx/sSsZFj+BFw/AyMWQ6snih2yLewGr64MoXmtKvw+sSM1KzuZpNGctoy9ncVTvxwlNSufpRM6ENBIueBzdWzyj1F7Tloa7/8/6DLZnKupziMmoviM7cCBA6af3OwRGLMSbkfBskeLzNyEEHyw/hxB524wfbA3k3o1NWsT3hydIzs0YM6IVuy7mMikP0+RW6DczM2s9rQgiulMvCgtAzpWlJZ3zDBqABkZGaadWLE6jN8oZdJZ/0KxmdvBS0m8ujIEv3pVWfliZ5ONGpjXlg1rVGTNS12oWcWJcUuOKzpz+8+PTW0+rH1WMmoD5phr1FTMoHwkQb68B1aOhjqt4JnNCAdnPtsSwS8Hr/Daw814q19LGWSaz6rjsby//hyDWtVh4Zh22OmJSVIxg+Qr8NtAyWP2uSCo2dzsS5qdBDkvU3rpuhkurSo07ETYtVRG/XSE+tUqsublLlR1sf4y1K20HEb8eJicfC3rJ3WzeqKBBw4hYNMrcPpPGPAFdH5ZjquqDxATKR9la5r2hhE/Q/xJWP8iP+69VLin9mbfFuZfH3l0ju7YkA8HeRN07gZf7bggg6rilJeSG7LrzE6B5U9K2WrGb5TFqAGkpJg5g6lQCZ5aI2UpWTmK65fO8uxvJ3CrKDkYyWHU5GjLWq7OLJvQkQKd4JnfjpOcmWf2Ne/nPzs2AQ58LRm1h96Vy6ipmEH5mLHd5fB3sGM6iwqGEOH3Dt+ObGtzsyIhBB9uCGPFsVjmjGjF6I7mLZWpANoCWPEkXDkgGTVP+fL8yVa2JvkKul/6cisbnuYzFk0aTLNa1skAUhonY5IZ+8sxfOq6suL5zrhUsE4GnQeKc+vgr4nQaqS03ypfYLxtPdzKEeVjxvYPFxo/wyrRl5cdAvm6cYisRk0unRqNhllDfenRvCbTN4RxKCpJluve5T/5Vrz9A8m1fsg3sho1kGHG9g9aN09mVJmBqy6NDe6LaVZdvuTJcrZle8/qzB/tz5m4FN77KxQ5X2z/k2Pz6hHYMAkadZOyJtlAMmqVcjRju5OZx9DvD1KQl8/e+j/hFLsPntsqa/4+OUnLyefJH4+QkJrNltd62Ex1gHLHiSWw5S0pp17/z2S/vFwzti+2RfLj3sus6HKNrqenQscXYdBXMihUhu/3RPHV9gvMeNSH57o1trac8kn6DVjUQ4prfD5YiXJHqpU0EcVnbIGBgWZfo0CrY8qKEG6m5vL9+I44jVoi7WmsfVaqGCADcui8F1dnRxaPD0AAU1aEyOYpKbdOpZBFZ/wpKU9j8/7Qd7b519NDamqq2dcIOpfAj3sv81SnhnQd9qJkhI8vhjMrZVCoTJ9P6tmUPt61+WxLBCdiyk6CYAj/qbGpLZBi1fIyYPRyq9bwUymO4jO2vLw8UaGCecsy3+y8yIJdl/jyidaMbN9A+uX1M1LWiUZd4em/wM68vYK8vDzM1amP7eE3eOmPU4zr3IhPhptfe04pnXJjts7sO7DoIenfL++XavgpQEBAAKdOnTL5/Es30xn2/SFa1qnCqhc74+RgLz30/hguVQaYuMPskkxK9Xlqdj7DFh4kM0/Llle7U8tVfwUEQ/nPjE2AnR/DofmSU1vrkfIIK446YzMRxWdshw8fNu/8y0l8t/sSI9rV+9eoAdRtC4O+hOg9Um5JMzFXZ0n0963DCz0a88fRq2w6e93s6ymlU27M0ikEbHwF0hPgyaWKGTUwI44NyMnX8sqK01SsYM+ipwMkowZSdfgnfoOKNWDNeKkashko1edVXRxZNC6AjJwCXll52uycp/+JsQlSzOKh+VJibOWMmooZKG7YWrVqZfK5tzNyeXP1GRrXqMQnw/TMdto9A22eksreRO8zQ6V5Osvi3QFetG9Ujff/CiU60fQHKSirU07M0nlsEUQGQt9ZUD9APlF6cHFxMfnc/wVFcOFmOnNHtqX2/bOdyu7w+BIpSXPQu2ZpVLLPveq48ulwP45fSWbRvstmXes/MTZT4uDvSVDXXwrCVrFJFDdsMTExJp0nhOCdtWe5k5nPd0/5U8nJofhBGg0Mniul3NowSVq+srBOQ3C0t+O7p/yp4GDHm6vPkK/VmXwtJXXKick6r5+BHR9J1a47K5+5IS/PtHiuXRE3WXbkKs93b0zPFu76D2rUBXq8A2dXSHkDTUTpPh/Rrh6PtqnLtzsvcibOdC/RB35s6nTSc0ZopRm5g+nZZFSURXHDVrNmTZPOW3Y4hj0XEvlwsHfpBT0rVJRiRzJuwpZ3TFRpuk5D8ajqwmfDW3E2PpWFu01Pwqq0TrkwSWd+Dvz9ElSqCcO+t4jrtIODnhemMriVlsPUdaH4eLgydUAZWW96vgf1O8DmN6XZmwko3ecajYZPh/tR29WZN1adJjO3wKTrPNBjE+DIQog5AAO/gOqqJ6kto7hhy8nJMfqc6MQM5myLpHdLd8Z3KbFs+r/Uawc934ewdVJRPxMwRaexDG7twQj/eizcE8XpWNNml5bQKQcm6dz9CSRGSvFAFvIy0+mMmz0LIXh77Vmy8gpYMMb/3321krB3kBwMhA7Wv2RSAV1L9HlVF0e+GdmGq8lZzNocbtI1HuixeeOcND69hkDbsfKLUpEVxQ1bfr5xVXy1OunB4eRgz5zHWxue2Lj7m1C/I2x526QKx8bqNJWZw3yp4+rMW2ukh6OxWEqnuRitM+YgHPke2k80uQSNKRjrFbzyeBwHLiXx4WAfwzOLVG8Mg7+G2MNw9EejNVqqzzs1qcHkXk1ZczKenedvGn3+Azs283PgrxckJ6ZHF6hB2OUAxQ1btWrGebQt3h/N6dgUZg/zLb4hXxr2DjDiJ2n9e9OrkmedgjpNxdXZka+fbEPM7Uw+D4ow+nxL6TQXo3TmpEl7F9U8od8nimnShzFLkfF3svhsy3m6Nq3B052MTJXWehS0HCy99SddMupUS/b564+0wKtOFT74+xwpWcbtPz6QYxNg7/8gMUJaHr+vdJaKbaK4YYuPjzf42As30vl250UG+tVhaJu6xt+sehOpsF/0HikhqREYo9NcujStwXNdG/Pn0ViORpdcRFUfltRpDkbp3PkRpMbDYz9JSYUtiKHOI0IIpq0/B8AXxqwk3EWjkVKCOTjDxilGLUlass8rONjx9ZNtSM7MY3bgeaPOfSDH5rUQOLwA2o2H5n2VE6UiK4obNi8vL4OOK9DqeGftWao4O/DpcD/Ta6u1nyjlbdv+IaQlyK5TLt7p34KG1Svy/l+hZOcZ/pCztE5TMVjnlf1waqmUraNhJ0U16cPZ2bBVgbtLkNMGeZueHq1KHRj4JcQdk0IaDMTSfe5XryqTezVlfcg1dkcaviT5wI3NgjwpnrJybej3qbKiVGRFccN24sQJg45bejiGc9dSmTnUlxpmFGXEzg6GfgfaXAh80+AlSUN1ykXFCg7MGdGKmNtZzAu+aPB5ltZpKgbpzMuCTa9BtcbQa5ryovSQmZlZ5jHXU7L5PCiCrk1rMNbYJcj7aT0SWgyEXbPhtmFxY9bo81cebkaL2pWZtv4cqdmG7Uk9UGMT4OA3cCschswD51I8s1VsDsUN28MPP1zmMXHJWczdcZGHvWoxpLWH+Tet0RQeng4XtxocP2SITrnp2qwmYzo24OcD0Zw1MH7IGjpNwSCde/8Hd67A0AVS2IYVcHV1LfOY2ZvPU6DTmbYEeT8aDQz5FuydYPPrBr14WaPPnRzs+frJNiRl5DFnq2F7wQ/U2LwZDvu/hlZPQssByotSkRXFDdumTZtK/VwIwccbw9BoYPYwX/MfHHfpPBnqBcDWdyGr7CSvZelUimmDvKlVxZl314UaFLhtLZ3GUqbO66eluKB246HxQ5YRpYeyytbsvXCLbeE3ePXh5vJVaHD1gL4zpZios6vKPNxafd66vhsTunmy8ngcJw1IlPzAjE2dTlpJcK4qVcNWKXdYvWxNYOh1XllxmumDvXm+RxN573wjDH56CPzHSsuTNsrO8zd54feTvD/Qi5d7NrW2HOXRFsDPvSAjEaYcAxc3q0kprWxNTr6W/vP2Y6/RsPWNHmXHrBmDTge/9ofky/DKSZvNDp+ZW0Dfb/ZRxdmRwNe642iv+Luw9Tm1DDa/Bo8thjajrKlEjSswEcVH6d9//13iZ6lZ+czcdJ5W9arybFdP+W9exw+6TIaQ3yH2aKmHlqZTafr61KavT23mB18i/k5WqcdaU6cxlKrzxC9SwOugL61q1KD0GdtP+6K5ejuL2cP85DVqIO0FPzoPclIlr9BSsGafV3JyYNYwPy7cTOfnA9GlHvtAjM2sZAieKTmgqQmOyy1WnbFNWx/KmpPxbJzSDb96Cm3O5mbA953A2RVe2g/2jsrcx0yupWTTZ+4+ujWryS/PtLe2HOVIvwkL20tppp7+y+rBriXN2GJvZ9H323308anN90+1U07AzhlwaB48GyR7dXA5efH3k+y/lMjON3s+2EVzN78OIX/Aywehto+11agzNhNRfMa2YcMGvb8/fiWZlcfjmNDNUzmjBuBUWapkfOs8HP2hxMNK0mkp6rm58Eaf5gRH3GRH+I0Sj7O2TkMpUefOj6EgR+oTG8jgoG/GJoRg5uZwHOw0fDRY4Ydbz/fAraHkwVugP6bOFvp85lBf7DUaPtoYVmK2FlvQaQgl6ow/JS1Ddp5kC0ZNxQwUn7HpdDphZ1fUfuYV6Bi04ADZeVp2vvUQFSsYn4jWaFY+JQVuTzkmPUiK6+R+nZYmX6tjyIKDpOfks/OtnnorGtiCTkPQqzPmECwdJGW8f6T05TdLoW/GtiP8Bi/+cYoPB3nzwkMy7/vq49JOWP6E5Mn70NRiH9tKn/9yIJpPt0Tw/VPtGKzHe9lWdJaFXp06Lfz8MKTfgFdOSCs81sf6b37lFMVH4e7du4v97rdDV4i6lcGsob6WMWogZeQG2Pqe3o/16bQ0jvZ2fPaYH9dTc1iwS3/aJVvQaQjFdGrzIegdqNoAerxtHVF6SEtLK/L/7Dwtszafp0XtyjzbzdMyIpr3BZ/hsO8rvbFtttLnz3b1xMfDlVmbw0nLKR7bZis6y0KvzlNLIeEM9P/MVoyaihkobtg6dOhQ5P8JqdnM33WJR7xq0centtK3/xe3BlIQ8IUgqQLufdyv01q096zOqPYN+OXgFSJvpBX73FZ0lkUxncd/lpaDB8yxWsyaPipVKprCa+GeS1xLyeaTYX6W9QAcMEeq7xU0tVhsm630uYO9HZ+PaEViRi5zt18o9rmt6CyLYjozk6SAec8e4Pe4dUSpyIri39zIyMgi//9sSwQFOsGMR32VvnVxOk+CWr5SReO8ohkn7tdpTd4f6IWrswPT/w5Dpyv6kLMlnaVRRGdaAuz5HJr1Ba/B1hOlh3tLmFxOzGDx/mhG+NejUxMLJ7t19YDeH8LlXXB+Y5GPbKnP2zZw4+lOjfjj6FXCrqUW+cyWdJZGMZ3BMyAvQypabAP7virmo7hhq1+/fuG/D19OIjA0gUk9m9KwhhXe2u0dpUS0afGw/6siH92r09pUq1SBaYO8OXn1Dn+FFE3Yaks6S6OIzp0fgTZPWg62sQdHhQoVAMlhZMbGcJwd7Zk2yNs6Yjo8D3VawbZpkjfvP9han7/TryXVKlZg+oaiL162prMkiuiMPSYlTO8yBdzLKBqrUm5Q3LDduSMV1MzX6vh4YzgNqrswqZcVg5AbdpYKBR5eCIn/5mi8q9NWeKJdfQIaVWPO1khSs/7dz7A1nSVRqPPKATi3Frq/IaU6szEKCqSaeFvOJXAwKol3+rXEvYoZuUrNwd4BBn8D6ddh378ZL2ytz6tWdOSDQd6ciUthzcl/ax/ams6SKNSpLYCgt8G1Hjz0rnVFqciK4obN0VGKG7vrMDJjiC/OjjIHuxpLn1nSPk/Q24X7GXd12gp2dhpmD/PlTlYec3f+u59hazpLwtHR8V+HEbeGUiFYG0Sj0ZCRW8AngefxrevK050NqNiuJA06gv/TUmjKLSlHoy32+Yh29ejoWZ052yJJzpTCFGxRpz4KdZ78VUoU0P9zKSxI5YFBccPm7OzMzbQc5gdbwWGkJCq7wyMfSyVTwtcDhpcvsSS+dasyrnMj/rxnP8MWderD2dlZKs2SGCmVanF0sbYkvdjZ2TE/+CI303L5ZLgf9nY2sFTaZzY4VYEt74AQNtnnGo2G2cN9Sc8p4Mtt0p6VLerUh7OzM2Tcgt2fQtOHwWeYtSWpyIzihi0pKYnPtkSQby2HkZIIeA482kp123LTSUpKsrYivbz1z37GRxul/Qxb1Xk/qXERsHcOtBgALQdaW06JZOXm8+uhGEZ3aEC7hjZSAbpSDXhkBlw9CKFrbLbPveq4MqGbJ6tOxBESe8dmdd5PUlKSlCggPwsG2kaiABV5UdywJdpVY9PZ69ZzGCkJO/t/9jNuwN45eHp6WluRXqq6ODJtkDenY1NYdyreZnXeT8urf0hLkQPmWPzeM2fOZP78+fz5Z+lV1IUQ3M4WuDo78N4AGyuS2e4ZqTrFjuk09rDNBMkAr/dpQW1XJz7aEEb9hlZexjWQZo634OxK6PYa1GxmbTkqCqC4YZu9JdL6DiMlUT8AAp6Boz8SfSTQ2mpKZIR/Pdo3qsacbZEcORVqbTllE70Pp0uB0OMtqN7YorcOCQnBxcWF119/nb1795KXpz9NFcDfp6+Rla/lvQFeVKtUwYIqDcDOTnI/z0wka8uH1lZTIpWdHPhoiA/h19NYEHTa2nLKRpuP/fb3/kkU8I611ZRIboHW2hLKNYobtusZwjYcRkrikRngXJWAmysNrrZtaSRHEj9SsvI4nG67b++AlO8waCrCzRO6vW7x22/dupVu3aRkws2aNeP48eN6j0vNzufzoAhcHO0Z2b6BJSUaTl1/6DCRete3QsJZa6spkcGtPOjRvCYbo3XcE3mLswAAIABJREFUSs8p+wRrcnwxlTOv2lyigPuZurYcvMDaMIrniqzu6Sua1LRNx4FCsm5DSixUawQutms4rqdkczsjj2a1KuNSwUZfFDJuQdo1ErVVcG9g+WWe2NhYatWqhbOzM4mJiTg4OFCtWtG9s8TERG5m5CMcK1GQeAV//7YW12kwOi3aG2HYV3CBmi2sraZEcgt0XLyRjlslRxpUs1GDoc2HWxFk6+xxqWdD+/33kZlbQHRSJnk3osKFEH7W1lMuEUIo+hMQECBsHq1WhL5WS4gvmwqRdcfaakokJStPeL6xUgxbeFBotTpryylOSrwQn3oIsWK0sFa/T548WURGRgohhFi0aJFYu3ZtsWPOxaeIxu8Hio83nBMVK1a0tESj+XhocyFmuApxcqm1pZSK18ipotF7geJwVJK1pehn3UQhZruLoT1aWVtJieQVaEXfb/aKrv/bJYCTQuHn84P6o/hSZGmFHG0GOzumH3GWZm57Pre2mhKp6uKI5uwGzsSlsPZUXNknWJodH4LQwoD/Wa3f69atW+idl5ycjIdH0Sz0Op1g+oYwqldy4q1+LdFqbX8vY3m4Fhp2lQpgZiVbW06J5J3ZTP1qLny8MYx8rc7acopyZf8/iQLeJPx66cV8rcnvR65y8WYGHz+qls0xB8UNm5ubdSskG8o1nTu0nwgnfrbp/YxqaVF08JQykqRklewYYXEu74Hwv6XM/dU8rdbvAwYM4PDhwwBERUXRsWPHIp+vPhnHmbgUPhjkRVUXR+ztbXRJ9x7c3KrB4K+latvBM60tp0SqVanEzEd9uXQrg18PXrG2nH/R5ksxgW6NoPsbNvtMupWew7ydF+nZwp1+thDvW45R3LC1b18+qkG3b98eHv5Q2mPb8g7obOyN8x86tG/P7GF+pOUU8JWeDOtW4R+HEao1hq6vAdbr94CAALKzs5k3bx69evUqkg0jOTOPL7ZF0rFxdR7zrwdAxYo2uh90D+3bt4favlIS75DfIe6EtSXppX379vTxqU0f71rMC77E9ZRsa0uSOPoDJF2Qits6utjsM2lOUCS5BTpmDvVFI8XWLba2pvKK4s4jgG26GpbEmRWwYRIMXQjtxllbTYnM2hzO0sMxbJzSjdb1rfwGevBbaSYxdp1UW8xGef+vUNaeiifotR60rFMF0F9o1GbJTYeFHaCSO7y4V4rFtEHikrPo++0+eresxY9PB1hXTOo1qc2a9IQxK62rpRROxCTz5KIjTOndlKn9C2Mq1chxE1F8xrZt2zalbyELhTrbjIGGXaRSFja4n3FX55t9W1CjkhQYe39pG4uSGg/7vgSvIUWMmq31e0jsHVadiGNCN89CowbFC43aIoVt6VRFymt4IxROLLGuKD3c1dmgekVe6d2MrWE32HvhlnVFbf+gcN/3LrY2Ngv+SRBft6ozU3qrAeNyoLhh69Gjh9K3kIVCnRoNDPoaslOk4oM2xl2drs6OfDjYi7Pxqaw+aUVHkm3vS/F//Ys63dhSv2t1go82hFHb1YnX+xR1ma9c2faT3xZpS9/HoEkvKc9hhpWNxn3cq/OFh5rQpGYlZmwKJyffSg46l3fD+Q1SIHY1z8Jf29LYBFh+LJaIhDSmD/GhYgUHa8t5IFDcsJ05c0bpW8hCEZ11/KDTS1K5+GunrKZJH/fqHN5WyrD+xbZI7mRawZHk4naI2Aw935ViAO/Blvr9z6NXCb+exkdDfKjsVPTBkZVlux5ydynSlndfvPKzYMdH1hOlh3t1OjnYM2uYL1dvZ/HTvmjLiynIlfZ9qzeBrq8W+ciWxuat9By+3nGB7s1qMtCvjrXlPDAobtiaNSsfU+tiOntNg8q1YMvboLMdl/B7dRbJsG5pR5K8LKkkjbsXdHml2Me20u/3PjgGt/Io9rmTk5VqrxlBsbas2VzKcxi6CmIOWkeUHu7X2aO5O4Nbe/D93iiu3s4s4SyFODgPbkdJLwGORasO2MrYBPg0MILcfB2zhxU6jKjIgGKGTaPRNNBoNHu6dOmCr68v8+fPV+pWBpOTk0PHjh1p06YNvr6+zJgxo/CzhISEogc7u0K/z+D6aZa/3Y9Dhw4RFxdH79698fb2ttrflJCQQFRUFO7u7nh6ejJ6wENknQli5bEYDkVes5yQA19L2VoGzwWH4nkWp0yZwr59+6zeXp8ERpBbUPzBsW3bNlq2bElERARz5lg+UbMxJCQk8NJLLxVpz4A3V5Jm5yZ58Grzy76IGZT2vblf57289NJL9KmRSn5uDr3f/hEfS42B25fhwFwymwyk9wufFht/xb7rVuLApUQ2nb3O5N5NaeJu+0vi5QqlIr8BD6BdVFSUSEtLE82bNxfh4eGlRt0rjU6nE+np6UIIIfLy8kTHjh3FkSNHhBBCREVF6TtBiN8Gi5RpbqIg9Ya4fv26OHXqlBBCWO1vuqtz+PDhYv/+/UIIIXo83Fe0nREkHv3ugCiwREaSW5FCzKohxPqXSjzE29tbxMfHW7W99kTeFI3eCxTzgy8W+X1BQYFo0qSJuHz5svD19RWtW7e2+tgsjaioKNGmTZti7flSrwZSRpKD8xW9f2nfm/t13stdzR+v2CcavRco/j4RrfwY0OmEWPqoEJ83EDeizuodf3q/6xYmO69A9Pxyt+j11R6RnVdQ0mFWz+BRXn8Um7EJIRKEECEAVapUwdvbm2vXrhWZbbRt25bq1avTtGlTi3inaTSaQmeB/Px88vPz0Wg0REVF0aFDh+Ka0tO57DWZSo4C+z2z8fDwoF27dtz/NylBnz598PPzK/azc+dOAMLDw/Hzk9LIXQwPZfoQH0LjU1l1IlYRPYUIAVveRuvggvfr6/T2Y0REBJ6entSrV89i7XU/2XlaPtoYRlP3SrzUs0mRz44fP06zZs1o0qQJGo2G0aNHs3HjRovoKonSvhdRUVG0aNGiWHsmuPqTWC1AqnuXqly7lva9uVdzQEBAkTFwV/P0kd1pWbsKXwVfoYVPK2XHwLm1cGUf9PmY2k1b6x1/MTExVnsG3eWHvZeJuZ3FJ8P8bDdBfHlGact5+vRpceXKFdGgQQORmpoqhCg62+jZs6cIDQ3V97aiCAUFBaJNmzaiUqVK4t133y38fe/evfVqmjt3rjj79TDpzfjq0cLj7/+bLMXp06dFVlaWaNCggRBCiNjYWOHj4yN0Op0YueiwaD1zu7idkaucgDMrpbY48WuJ/Th37lwxY8aMIqdZur3mbI0Qjd4LFEcvF89buHbtWjFx4kQhhDSz/P3338WUKVMsoqs0SmrPt956SyxZsqTIsXfbMy32nBCf1BJi9XhFtZX0vblXc0BAQJExcK/mY9G3RaP3AkXDIa8oNwaykqV8r4t7C6EtOgu6d/ydPn3aqs+gqFvpovkHQeL1lSFlHWr1mU95/TFrxqbRaII1Gk2Ynp/CWuuurq48/vjjzJs3D1dXV6DobCMyMpKWLVuaI6MIJc107r6R29vbc+bMGeLj4zl+/DhhYWEAXL16Va+m7du34/7EV+BaD4LeBm0BGRkZxf4mS+Hh4cH58+fx9vYGICIiAm9vbzQaDZ8M9yMzt4DPtkQoc/OsZKnieP0O0O6ZEvtx+/btPPbYY4WnWbq9Im+k8fP+aEa2r0+nJjWKfS7Ev3F/dzOT2MLGfUntGRISwoABAwqPu7c9qzTwk9KYnd8AUbsU01bS9+ZezbGxsUXGwL2afdwr4HT9NA5+/bmVo9BCUfAsaYwOmVckeP3+8efh4aHoM6g0hJBCT5wc7fhwsJoPUinMCpoQQvQp7XONRuPYsWNHxo4dy4gRIwDIzs4mJyeHatWqERcXR40aNahQQb4ij8HBwQYd5+bmRq9evdi2bRtNmzYlIyOjmKasrCxSUlLwaNRcitNa+wzaY4t5fNbGIn+TJYmKiuLy5cuFX0oXFxdCQkKIjIzEy8uLFx9qwg97LzPcvy49mrvLe/PgGZCdDIP/Jjs3V28/3m2zjIwMQFq6evzxxy3WXjqd4IP153B1cWTaQG+9x9SvX5+4OCn2Lzc3l/j4eOrWrau4ttIo6XuRlZXFzZs3C/Xpbc+ur0kVoYOmwuQj4KCcp+f935t7NVeqVKnIGLhf87i+g1iT4cjHG8NY/nwneV8m4o7Dqd8kD12P1oW/1tde4eHhij6DSmPDmWscvnybT4f74V7F9j1yyytKekVqgCXt27fnrbfeKvy9vtmGpUhMTCzMOp+dnU1wcDBeXl6cP3+eVq1aFdO0Z88eevfuLZ3sMwzRpDe52z6ik0+jIn+TJWnbti3jx49n7ty5gBRsGh0djZeXlIbntUea07hmJT74+xxZeQXy3Th6r5SnsOur4NG6xH6822Zt27ZFCMHEiRPx9va2WHutPBFLSGwK0wd7l1gVu0OHDly6dIkrV67g4uLCqlWrGDp0qEX0lURp7Tlw4ECAktvT0Vlya0++DIcWyK6ttO/NvZrbtGlTqPnu9+ZezdPfeZ2p/Vty+PJtNofK6JlYkAeb35BWVXpNK/x1Se1VoUIFqzyDbmfk8mlgBG0buPFUx4YWued/FSXj2LoB44KCgmjbti1t27YlKCioyBLAvbMNS5CQkEDv3r1p3bo1HTp0oG/fvgwZMoTw8HCqVq1aTNPWrVv/XU7RaDhVZwwabT4PZ22ibds2hX+TJTlw4ECpnzs72jNnRCvikrP5ZsdFeW6alwmbX4fqTQsfHCX14902O3DgAIcOHeKPP/5g9+7dRcaAUtxMy2HO1ki6Nq1RmORYHw4ODixcuJD+/fsTFhbGyJEj8fW1buHJ0tqzdm0p03up7dnsEfAZJoVhJMubWb+07829mo8dO1bse3O/5q8nPUbDyvBp4HnSc2QKUzj4DdwKl0JPnP51my+pvTZs2GCVZ9CszedJy8nni8dbY2dn/aXvBxoLbOSVW/z9/UVeXl7RXx5aIDlPnF1jHVEGMm19qGj8fqA4EytD4dSt06S/+crBMg/V22YWQKfTiQm/HRctpweJ6MQMg8+z9UK4RrVnSrwQn9UT4rfBQmi1ygorhbI0n469IzzfDxQfrJfBYSPhnBCzqgux7nnzr6Ug28MS9IaelIHVnTDK64/imUfWr1+v9C1kQZ/OkJCQImVPAOg8WXKe2DrVKrn6DG3P9wd64V7Fiff+CiW3wIzMKXEnpLIf7SeCZ7cyD7/bZpbu9/Uh19gVeYup/b1oXLOSwefZeiHckJAQNm/ebNjBVetB/08h5gCctHyS5Lt9rvd7cw9tG7gxsVtjlh+L5eClJNNvqM2HjZPBpRoM/MJonZYiNSuf6RvC8PZwZVKvpha9938VtWyNKSRegEU9oEV/GPWHtdWUyO7Im0xYepJJvZry3gCvsk+4n/wcWNwTcjMkpwRny3qAGsrNtBz6frOPlnWqsPrFLkYt85SrsjWGIAT8OQJij8GkQ1C9sbUV6SUnX8ugBQfIzdex7Y0eVHEu2RCWyP6vYfcnMPJ3aRnWRpm69izrT19j45Ru+NWrasyp6nqliagztn8wSqd7S+j1PkRsgrC/lBOlB2N0PuxVm1HtG/DTvsucumpCCZ5dsyExEoYuMNqoWarfhZC8IPO0Or58oo3Rexe2PmMDI9tSo4FHF4DGDja+YtGCucbodHa05+sn25CQmm1aeMrN87DvC8mgGWnULPlM2h15k7Wn4nm5ZxNjjZqKGagzNlPRFsCv/aS8dJMOS8tANkh6Tj4D5h3A0V5D0Os9DC+LEb0Xfh8GHV+UKg/bKGtPxjF1XSgfDfFhYnfjZycP3IztLqeWwebXYOCXUqUKG2XO1kgW7bvM0uc60KtlLcNOKsiFnx+G9Bsw+ShUljmsRSaSMnIZMG8/NSs7sfGVbjg5GJ1hRJ2xmYjiM7bAwEClbyELRuu0d4ARP0vr/BtettibsbE6qzg78vWTbYi5ncWcrQZ6fmWnwIbJUKM59JllgkrL9HtMUiYzNoXTqXF1nuvqadI1UlNT5RWlACa1Zbvx0KwP7PxYmt1YAFN0vtGnOc1rVebddaHczsg17KRds+FmGAz73iSjZomxKYTgvXWhpOUUMH+0vylGTcUMFDds/fr1U/oWsmCSzhpNYeAcuLIfjiyUX5QeTNHZpWkNJnRrzO9HrrLHkIrGW9+V3oZH/AQVKpqgUvl+zyvQ8dqq0zja2/HtqLYmu09bOnOMKZjUlhoNDPtBqrr910TIz5Zf2H2YotPZ0Z75o/1Jycpn6rpQylxBurxH+q61nwgtB5R+rIw6jWX5sVh2Rd7i/QFeRSq2q1gGxQ3b4cOHlb6FLJis038ceA2R3iITQuUVpQdTdb47oCVedarw9pqz3EjNKfnAs6shdLVUPLRegIkqle/3b4MvEhqfypwRrajr5mLyde5mSLFlTG7LKrVh+I9w67xFipKaqtOnrisfDPJid+Qtlh2OKfnArGTYMAlqtoB+n5omEuXH5uXEDD7dcp4ezWvyrIkrCSrmobhhu5vRw9YxWadGA0O/g4o1YN0EyE2XV9h9mKrT2dGe78e2Iydfy2srT1Og1bN0eisSAt+Ahl2hxztW0WkIh6OSWLTvMmM6NmCgnuKhxuDiYrpRtBRmtWXzvtB5Cpz4GSKVTSZgjs5nunryiFctPg+K5Px1PVn2dTrYOAUyk6QtABNXEszVWRbZeVqmLA8pdI5RA7Gtg+KGLSYmRulbyIJZOitWh8d/llIabXxFcrlWCHN0NnWvzGeP+XE8Jpn5uy4V/TAvE9aMB8eK8MSv0h6ilXSWxs20HF5ffYbGNSvx0RDzk8jm5eXJoEpZzG7LPjOgTmvJMKQoV9bIHJ0ajYavnmyDW0VHXl0ZQmbufengDs2DC0HQdzbUbWs1naUhhGD6hjAu3Ezn21Ftqe3qXPZJKoqguGGrWbOm0reQBbN1Nn4IHpkhZVk/+oM8ovRgrs7H/OvzZEB9Fu6J4sClROmXQkDgW5B0ER7/BVzNmwXJoVMfeQU6Ji8PISOngB/HBhju4VkKDg7mX0NpzG5LByd44jfQFcDqpxXbbzNXZ/VKFZg3ui1XkjJ5Z+3Zf/fbovdK8Wq+I6DzJKvrLIlVJ+L4KySeVx9uTm9DPTxVFEFxw5aTU8p+jg0hi85ur0v7bTs+gqvKrOPLoXPWMF+a16rMKytOE5OUKWVFD10lxeY17S2DSmX6fXZgOKeu3uGrJ1vLtiGvs2Ccl6nI0pY1m8GIxZBwVkoYrMCqghw6uzatyQeDvNkadoPv90RJBVTXTZQ8dId+Jy3924DO+zkXn8qMjeH0aF6T1x9pLvv1VYxDccOWny9TolOFkUWnRgPDf4BqnrD2WUWqGsuhs2IFB34Z3wE7DSxc8gsiaCo0fQQemiqDQgm5+33NiTj+PBrLiw81YUhr+UrMWCCO02xka8uWA6HXB9JLzLFF8lzzHuTSObF7Y4a3rcvCnWGkLhsDBTkw6s8iCY7NQe6xmZiey8t/nqJm5QrMH+2PvbqvZnUUN2zVqlVT+hayIJtO56rSlzAvC1aMhBx5y83LpbNhjYr8OsSNj7PmcN2+HgUjlhQpzmgucvb7iZhkpm8Mo1uzGrzbX96CkOVhKVLW79BDU6VVhe0fSq7zMiKXTo1Gw5wRfvxS5WeqJp8lofe34N5ClmuDvO2ZlVfAxGUnSM7MY9G4AKqXUCpJxbIobtji4+OVvoUsyKqztg+MXCalo1ozTqoXJROy6cy8jf+BF6jg5MyojLf4bPd1ea77D3LpvHgznYlLT1DPzYXvxrTDwV7eIVsenEdkHZt2dlIIgHtLWD0Orp+R7dJy6nTePYPueYf41u4ZnthXs/QQFSORS6dWJ3ht5WnCrqWyYIw/reu7yXJdFfNR3LDdLYBp68ius9kjUs6+6L1SaiOZlrxk0ZmXCauegrQEnMetpm/XDvx2KIaFuy+Vfa6ByKHzeko2z/x6HCdHe36f0FGRt2FnZ9v3XJN9bDq7wtN/gYsbLH9CSgsnA7LpPPojHP0eOr5E3wmzSc3OZ9ySY6RkyfMSIodOIQSzN4cTHHGLGY/60tentgzKVORCccN24sQJpW8hC4ro9B8rFeY8u1JKbSSDcTNbZ14WrBgF8celzCINOvLRYB8e86/H1zsusuSgPEUqzdWZkpXH+F+Pk5FTwLLnOtKguulxS6WRmZmpyHXlRJGx6VoXnl4POq1UDSD9ptmXlEVn6BrYNk1aLh3wP/zqu7F4fABXb2fx3NITslSFN1enEIJvgy+x7MhVnu/emGfUIGybQ/EkyDqdTtjZKW4/zUan06GITiFgy9tSfazOk6H/52Z5dpmlMz8bVo6G6H3w2E/QZlThRwVaHa+sOM228Bv8b0QrxphZut4cnUkZuYxfcpyoWxksm9CRLk1rmKWlNMpDEmTFxiZA/ClY9ii4NYTxG6BKHZMvZbbO08ulWLtG3WDs2iJB2NvCbjB5+Sm6NavJT+PMC/UwR6cQgrk7LrJwTxRPBNTnS2WrYateKCaiuMXZtGmT0reQBcV0ajRSyfpOL0vxbUHvmJUw2WSd+Tmwaqxk1Ib/UMSoATjY27FgjD+9Wrrzwd/nWHncvEBeU3UmpGYz8qcjRCdl8NP4AEWNGpSPsjWKfofqB8BTq6TA7V/7Q7LpM3azdJ78TSoa2qRXMaMGMMCvDl8+0YZDUUk8/Yt5y5Km6hRC8MW2CyzcE8XoDg2UNmoqZqCWrbEUQkjLkYcXgP/TMGQe2JtQXNEUspJh5RiIOyrFArUbX+KhOflaXv7zFHsvJDK1f0sm92qKRobYIUOIScpk7C/HSM3O59dnO9CxcXXF71keZmwWIf4ULH8c7J1g3N+SA5SlOPIDbJ8GzfvByD/AseR9z21hCby28gyeNSvy+4RO1KlqmT1SrU7wSeB5lh6OYWynhnwyzM8SRk21miai+Izt77//VvoWsqC4To1GSgfU8z04/Sf8+Thk3zH6MkbrTLwIS/rB9RAp+0QpRg2knJI/j2/PsLZ1+Wr7BaauCyW3QKu4zuNXknli0WGy87WsfKGzRYwalI8Zm0W+Q/UD4Lmt0jj9baBJoQBG69QWSMv026eB96MwanmpRg1ggJ8HS5/rwLU72Tz+42EibxgfTmOszozcAl78/SRLD8cwsXtjPh1uEaOmYgbqjM0anF4Om1+XNvCf/M2sLPqlcn4jbJgipVQa+Tt4djP4VJ1OMH/XJebvukSb+lX5bkw7GtaQ34FDpxP8djiG/wVF0LB6RRaPb0+zWvIE4hqCOmO7jzsxsGI0JF2Ahz+SsunIGN9YSGq8lFEk7ih0fQ36zDTqPufiU5m47ATpOQV8PsKPx/zry68RiEhIY8ryEGJuZzJrqC/jungqcp8SUK2niSg+Y9uwYYPSt5AFi+r0HwvPBUkeaUv6w74vDY51M0jn3UKha8ZDzebw0j6jjBqAnZ2GN/u2YNHTAUQnZTJ4wQFWn4g1OFOHITqvpWTz7NITfBJ4nl4ta7HhlW4WNWpQPmZsFh2b1Tzh+WDwGQ67ZsGyoZKxMwCDdAohlUZa1F0qFjriF+j3idHGs1X9qgS+1p1W9avy5uqzTFkRQnKmfN8hrU7w077LDPv+EBm5Bax4obOljZqKGahekf+gqOdZSWQlS0sx4evB3VuqMdXskVK9JkvVqS2QQguCZ0J2MvR4W1r6NHMvLy45i7fXnuX4lWQ6Nq7O9MHeZQajlqYzO0/Lb4ev8N2uKASC6YN9GNupocX28u6lPMzYrDI2hZDGUtC7oMuH7m9Cl1dKTWtVps4b56Q8qtF7oH4HGL5IymFpBgVaHYv2XWZe8CUqOzvwdr+WjO7QAMdSAvnL0nnk8m0+3XKe8Otp9POpzWePtcK9ipNZOk1EnbGZiOKGLTg4WPTp00fRe8hBcHAwVtMZGSTtM9yJgYZdpAdIiwF6S8fo1ZmbAWHr4NACqXRO/Y4w+GvwaCObRJ1OsPpkHF9tv0ByZh59fWozoVtjOjeprtcg6dN5OyOXtafiWXLwConpufTxrs3MoT7UrybvEufq1asZNWpU2QcCLVq04OLFi7LeX26sOjZTr8GO6dLLV8UaUnZ9//FSEdP70KtTCIg7LgVcn98kpZzr/QF0eF7WJc4LN9KZuSmcI9G3aVDdhRd7NGGYfz1cnYu/1OnTqdUJ9l9MZPH+aI5E36aemwvTBnkxuJWHVV64/kE1bCaiuGFLTU0VVatWVfQecpCamopVdRbkwqmlcHghpMZCxZrgNVgqh+PRRoozcnAiNSWFqi4OkBwNCWcgahdEBUNeBtRpBT3fh5aDpNRJCpCek88vB67w+5EY7mTlU8/Nhf6+dejYuDq+dV2pU9UZR3s7UlJS0FSoRHRSBqHxqey5cIvDUbfJ0+ro0qQGb/ZtoYiDyObNm/nhhx/YunWrQcf7+/tz+vRp2XXIidXHJkDcCdg3Rxprdg7SuGzWV9ofdm8Bzm6kpqVRtXIlSLsmVe2+eggiAuHOFcmgtZ8g7dm5KJM/VgjBngu3WLArijNxKTg72tGrRS16tKhJ63puNHavRKUK9qSlpVGxchXikrOISEjnSHQS28NvkpieS21XJyZ2b8z4Lp44Oyqwt2gcqmEzEcUN27Fjx0SnTp0UvYccHDt2DJvQqS2Ai9ukGdilnZLBuot9BXQ6gZ24Jzt55TrQor8UQlC/gyxlPQwhJ19LYGgCW0Kvc+gfgwXS7R3t7dBqdWjvGVqNalSkr3dtRnZoQIva8pScKYlnn32WpUuXGnSst7c3ERERiuoxF5sZmwBJUXD6D4jcArfvScFm54AOO+x0+RT6i9k5Snu7fo9LtdRkys5fFkIIzl1LZc3JOHZF3CLhnjyTjvYaEIL8e0JJK1awp3uzmgz3r0cf79pUcLCZrRPVsJmI4obt2rVrol69eoreQw6uXbuGzenUFsDNc5LLfspVyMskPT2dKrUaglsDqN1Kcg6x3lIJIBm58OsKL++8AAABfElEQVSpRN3K4HpKDjkFWjLTM/D0qEH9ahVpVb8qdas6W2xJpyzDtnjxYhYvXgzAjRs3bD5Rt02OTZA8G2+ck3JNZiWRnpZKlWruULU+1GgGdf3B0cWqEoUQxNzOIjIhjZjbWaRm55Oenk7tGm7UdXOhWa3K+NZ1LXVPzoqohs1EFDdsYWFhws/PT9F7yEFYWBiqTvmwhM7t27cTFxdX+H8vLy+6d+9u1IzN19eX8PBwhRTKg9rn8lJedKIaNpNRvBiVo6OFsmuYiapTXiyhs3///mZfw4qOAQaj9rm8lBedKqaj+Py7PJQFAVWn3JQXneUhFKW8tKWqU8VWsETmERUVi6HRaIYBC4AXhBA7DDh+mxBigPLKVFRULIVq2FRUVFRUHihsfx1GRUVFRUXFCFTDpqKioqLyQKEaNhUVFRWVBwrVsKmoqKioPFCohk1FRUVF5YFCNWwqKioqKg8UqmFTUVFRUXmgUA2bioqKisoDhWrYVFRUVFQeKP4POVD5LDcYv3IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## 设置刻度范围和刻度标签\n",
    "\n",
    "x = np.linspace(-2*np.pi, 2*np.pi, 200)\n",
    "y_1 = np.sin(x)\n",
    "y_2 = np.cos(x)\n",
    "\n",
    "plt.subplot(211) # 2行1列，指定第二个子图\n",
    "# 1. 刻度以圆周率形式展示\n",
    "# 2. 设置合理的范围\n",
    "plt.xlim(-2*np.pi, 2*np.pi)\n",
    "plt.xticks([-2*np.pi, -1.5 *np.pi, -np.pi, -0.5*np.pi, 0, 0.5*np.pi, np.pi, 1.5*np.pi, 2*np.pi],\n",
    "\t\t[r'$-2\\pi$',r'$-3\\pi/2$',r'$-\\pi$',r'$\\pi/2$',r'$0$',r'$\\pi/2$',r'$3\\pi/2$',r'$2\\pi$'])\n",
    "\n",
    "plt.plot(x,y_1, label=r'$\\sin(x)$')\n",
    "plt.plot(x,y_2,label=r'$\\cos(x)$')\n",
    "plt.grid(axis='x',color='gray',ls=\":\")\n",
    "plt.legend(loc='lower left', bbox_to_anchor=(1,0.5,0.9,0.9))\n",
    "\n",
    "\n",
    "ax = plt.subplot(212)\n",
    "# 1. 取消两个轴\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "# 2. 移动两个轴\n",
    "ax.spines['left'].set_position(('data', 0))\n",
    "ax.spines['bottom'].set_position(('data', 0))\n",
    "\n",
    "ax.set_xlim(-2*np.pi, 2*np.pi) # 这里通过ax设置,也可以通过plt设置\n",
    "plt.xticks([-2*np.pi, -1.5 *np.pi, -np.pi, -0.5*np.pi, 0, 0.5*np.pi, np.pi, 1.5*np.pi, 2*np.pi],  # 这里通过plt设置\n",
    "\t\t[r'$-2\\pi$',r'$-3\\pi/2$',r'$-\\pi$',r'$\\pi/2$',r'$0$',r'$\\pi/2$',r'$3\\pi/2$',r'$2\\pi$'])\n",
    "\n",
    "plt.plot(x,y_1, label=r'$\\sin(x)$')\n",
    "plt.plot(x,y_2,label=r'$\\cos(x)$')\n",
    "plt.grid(axis='x',color='gray',ls=\":\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## 设置刻度范围和刻度标签\n",
    "\n",
    "x = np.linspace(-2*np.pi, 2*np.pi, 200)\n",
    "y_1 = np.sin(x)\n",
    "y_2 = np.cos(x)\n",
    "\n",
    "plt.subplot(211) # 2行1列，指定第二个子图\n",
    "# 1. 刻度以圆周率形式展示\n",
    "# 2. 设置合理的范围\n",
    "plt.xlim(-2*np.pi, 2*np.pi)\n",
    "plt.xticks([-2*np.pi, -1.5 *np.pi, -np.pi, -0.5*np.pi, 0, 0.5*np.pi, np.pi, 1.5*np.pi, 2*np.pi],\n",
    "\t\t[r'$-2\\pi$',r'$-3\\pi/2$',r'$-\\pi$',r'$\\pi/2$',r'$0$',r'$\\pi/2$',r'$3\\pi/2$',r'$2\\pi$'])\n",
    "\n",
    "plt.plot(x,y_1, label=r'$\\sin(x)$')\n",
    "plt.plot(x,y_2,label=r'$\\cos(x)$')\n",
    "plt.grid(axis='x',color='gray',ls=\":\")\n",
    "plt.legend(loc='lower left', bbox_to_anchor=(1,0.5,0.9,0.9))\n",
    "\n",
    "\n",
    "ax = plt.subplot(212)\n",
    "# 1. 取消两个轴\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "# 2. 移动两个轴\n",
    "ax.spines['left'].set_position(('data', 0))\n",
    "ax.spines['bottom'].set_position(('data', 0))\n",
    "\n",
    "plt.xlim(-2*np.pi, 2*np.pi) # 这里通过ax设置\n",
    "plt.xticks([-2*np.pi, -1.5 *np.pi, -np.pi, -0.5*np.pi, 0, 0.5*np.pi, np.pi, 1.5*np.pi, 2*np.pi],  # 这里通过plt设置\n",
    "\t\t[r'$-2\\pi$',r'$-3\\pi/2$',r'$-\\pi$',r'$\\pi/2$',r'$0$',r'$\\pi/2$',r'$3\\pi/2$',r'$2\\pi$'])\n",
    "\n",
    "plt.plot(x,y_1, label=r'$\\sin(x)$')\n",
    "plt.plot(x,y_2,label=r'$\\cos(x)$')\n",
    "plt.grid(axis='x',color='gray',ls=\":\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\n\\nset_position(self, position)[source]\\nSet the position of the spine.\\n\\nSpine position is specified by a 2 tuple of (position type, amount). The position types are:\\n\\n'outward' : place the spine out from the data area by the specified number of points. (Negative values specify placing the spine inward.)\\n'axes' : place the spine at the specified Axes coordinate (from 0.0-1.0).\\n'data' : place the spine at the specified data coordinate.\\nAdditionally, shorthand notations define a special positions:\\n\\n'center' -> ('axes',0.5)\\n'zero' -> ('data', 0.0)\\n\\n\""
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "\n",
    "set_position(self, position)[source]\n",
    "Set the position of the spine.\n",
    "\n",
    "Spine position is specified by a 2 tuple of (position type, amount). The position types are:\n",
    "\n",
    "'outward' : place the spine out from the data area by the specified number of points. (Negative values specify placing the spine inward.)\n",
    "'axes' : place the spine at the specified Axes coordinate (from 0.0-1.0).\n",
    "'data' : place the spine at the specified data coordinate.\n",
    "Additionally, shorthand notations define a special positions:\n",
    "\n",
    "'center' -> ('axes',0.5)\n",
    "'zero' -> ('data', 0.0)\n",
    "\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linspace(1,1,10)"
   ]
  }
 ],
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